An artificial intelligent single cell is part of the cell dream world

Cell biology and toxicology has in recent years received a tremendous growth of interest which has resulted in a disparity between the speeds that the technology and science has advanced in when comparing with its increased attention and importance. There are a multitude of factors that has led to this disparity such as a more complex cell structure that we initially imagined. Biological functions of a cell can be described in depth through integration of trans-omics with systems biology, on which the concept of clinical trans-omics was coined after fusing molecular multiomics, e.g., genomics, proteomics, and metabolomics, of cells/tissues harvested from patients with clinical phenomes (Wang X. 2018). With the development of the Human Cell Atlas project (Regev et al. 2017), the single-cell biology and systems biology will be painted out by measuring highthroughput single-cell molecular profiling. It is possible to identify single-cell characters involved with metabolic networks or signaling networks as well as complex interactions within the cell as an intact biological system. The early concept of single-cell biology was proposed for the discovery and development of diseasespecific biomarkers (Niu et al. 2016), although we did not understand how to link single-cell measurements with clinical phenomes in order for patients’ to reap the benefits of molecular therapies. Niu et al. (2016) tried to tell a story of single-cell systems where molecular profiles (e.g., gene and protein expression and sequencing) as well as their networks and interactions could be well defined and organized into a larger picture. Based on the knowledge of single-cell biology, computerized whole-cell models may be developed and established with the capacity for auto-learning for intelligent medicine and precision medicine. Furthermore, we call your special attention to think of the artificial intelligent (AI) single-cell as an optimal systemwith full understanding of cell molecular profiles, intelligent capacity for functioning and deep learning, and precise interpretation of measurements. Such an AI single-cell system could be expected to translate the message between single-cell molecular profiles and clinical phenotypes, explain alterations of single-cell gene/protein expression and networks in patient response to therapies, and act as a decision-making assistant for disease diagnosis and monitoring. Artificial intelligent single cell is defined as a single-cell-like system with computerized databases, digitalized informatics of biological elements, and programmed function and signals. Koch recently Cell Biol Toxicol (2018) 34:247–249 https://doi.org/10.1007/s10565-018-9433-1